Cell motility and migration as determinants of stem cell efficacy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Stem cells` (SC) functional heterogeneity and its poorly understood aetiology impedes clinical development of cell-based therapies in regenerative medicine and oncology. Recent studies suggest a strong correlation between the SC migration potential and their therapeutic efficacy in humans. Designating SC migration as a denominator of functional SC heterogeneity, we sought to identify highly migrating subpopulations within different SC classes and evaluate their therapeutic properties in comparison to the parental non-selected cells. METHODS: We selected highly migrating subpopulations from mesenchymal and neural SC (sMSC and sNSC), characterized their features including but not limited to migratory potential, trophic factor release and transcriptomic signature. To assess lesion-targeted migration and therapeutic properties of isolated subpopulations in vivo, surgical transplantation and intranasal administration of MSCs in mouse models of glioblastoma and Alzheimer's disease respectively were performed. FINDINGS: Comparison of parental non-selected cells with isolated subpopulations revealed superior motility and migratory potential of sMSC and sNSC in vitro. We identified podoplanin as a major regulator of migratory features of sMSC/sNSC. Podoplanin engineering improved oncovirolytic activity of virus-loaded NSC on distantly located glioblastoma cells. Finally, sMSC displayed more targeted migration to the tumour site in a mouse glioblastoma model and remarkably higher potency to reduce pathological hallmarks and memory deficits in transgenic Alzheimer's disease mice. INTERPRETATION: Functional heterogeneity of SC is associated with their motility and migration potential which can serve as predictors of SC therapeutic efficacy. FUNDING: This work was supported in part by the Robert Bosch Stiftung (Stuttgart, Germany) and by the IZEPHA grant.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it